Many scientific questions require estimating the effects of continuous treatments, which relationships with an outcome are usually described by dose-response curves. Outcome modeling and methods based on the generalized propensity score are the most commonly used methods to evaluate continuous effects. However, these methods may be sensitive to model misspecification. In this paper, we propose Kernel Optimal Orthogonality Weighting (KOOW), a convex optimization-based method, for estimating effects of continuous treatments. KOOW finds weights that minimize the penalized weighted functional covariance between the continuous treatment and the confounders. By minimizing this quantity while simultaneously penalizing the weights, KOOW successfully provides weights that optimally orthogonalize confounders and the continuous treatment. We describe its properties and valuate its comparative performance in a simulation study. Using data from the Women’s Health Initiative observational study, we apply KOOW to evaluate the effect of red meat consumption on blood pressure.